CMKL University is seeking a passionate and forward-thinking Lecturer or Assistant Professor to contribute to the teaching and research of cutting-edge subjects in Software Engineering and Applied Artificial Intelligence, helping us prepare the next generation of innovators and engineers.We are particularly looking for individuals with a strong foundation in AI engineering, application development, and the deployment of real-world intelligent systems. Candidates should be passionate about both technical excellence and education, and eager to contribute to our collaborative, interdisciplinary environment.Areas of Teaching and Expertise (Preferred):
- Fullstack / Multi-platform Application Development
- Practical AI Engineering
- Data Engineering & DataOps
- Software Architecture & System Design
- DevOps, CI/CD & Automation for AI
- ML Lifecycle & Deployment Strategies
- Cloud-native & Serverless ML Deployment
- Containerisation & Orchestration (e.g., Docker, Kubernetes)
- Model Security & Governance
- Agent-to-Agent Communication / Contextual Protocols
- Proficiency in Python, TypeScript, C++, or Rust
Key Responsibilities:
- Design and deliver undergraduate and/or graduate-level courses in the areas above, for both traditional students and professional learners.
- Develop engaging course materials, assignments, and assessments that align with industry standards and emerging technologies.
- Continuously review, improve, and innovate curriculum to keep pace with the fast-evolving AI and software engineering landscape.
- Conduct academic research or applied projects in collaboration with faculty, industry partners, and government agencies.
- Supervise student projects, theses, and provide academic mentorship and career guidance.
- Participate in university-wide committees and contribute to strategic initiatives, including curriculum innovation, industry collaboration, and lifelong learning programs.
Qualifications:
- Master’s or Ph.D. in Computer Science, Computer Engineering, Software Engineering, or related field.
- At least 2 years of relevant professional or academic experience in one or more of the following areas: AI Engineering, Application Development, Data Engineering, ML/AI Ops.
- Proficiency in one or more programming languages such as Python, JavaScript/TypeScript, C++, or Rust.
- Familiarity with:
- ML Lifecycle and Deployment
- Model Versioning (e.g., DVC, MLflow)
- CI/CD for Machine Learning
- Containerization (Docker, Kubernetes)
- Serverless ML Deployment on Cloud Platforms (AWS, GCP, Azure)
- Model Security Practices
- Experience in Full Stack Web Development or DevOps is a plus.
- Demonstrated interest or experience in teaching and mentoring, especially across diverse learner profiles including undergraduates and professionals.
- Strong communication skills and a collaborative mindset.
